ASMI

ASMI removes the friction of real-time purchasing of content inside the video.

ASMI has a software that is in the pilot stage with several major OTT platforms and social media platforms using heavy amounts of user-generated content.

ASMI can work with any provider of video content: telecommunication companies, short video apps, ad platforms, e-commerce providers, and many more!

ASMI team estimates the TAM at $100B.

It is immensely difficult to monetize user-generated content; and, as this type of content is quickly becoming the dominant form of video being watched amongst young age groups. Young age groups are the future users of an advertisers products. Advertisers want to target users, but their current array of advertising measures are both inefficient and expensive. ASMI believes this can be solves by targeting the video user with the right product in the video they will buy, and giving them the option to buy it instantaneously!

ASMI is a B2B SaaS company using computer vision and behavioral pairing software to eliminate the friction of real-time purchasing inside video content to create transactions precisely when the user's interest has peaked.

Mirriad, Ryff.co, Google, Facebook, YouTube,

ASMI software has five unique and proprietary components: automated ads, content injection, clickable ads, in-Ad purchase capability, ads that cannot be blocked.

ASMI works off 85-90% margins.

ASMI plans to work with video content providers as a software tool to work on top of their existing ad platform.

The completion of 10 customers and conservatively converting 3 customers each of which would provision $1M+ ARR for ASMI.

$2M investment at a $6M pre-money valuation

An incumbent is able to combine all five components into one service, which is estimated to be very difficult. ASMI has patents patending covering each component.

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One of the best "two person pitches" in the history of an angel consortium (in due diligence with that angel consortium).

“Video Analytics and Content Injection Mechanism” -- Filed in May 2019

“Behavioral Pairing and Click Through Capability of Embedded Ads” – Filed in December 2019